Spike Model Research Articles

The Public Willingness to Pay for Reducing the Incidence of Hazardous Chemical Spill Accidents by Half in South Korea

Hazardous chemical spill (HCS) accidents, which occur due to careless workers, transport accidents, etc., can be harmful to humans. Recently, an average of 96 cases of HCS accidents have taken place in South Korea annually. As a result, the government is trying to reduce the incidence of HCS accidents by 50%. Government officials are seeking information about the value that the enforcement of the reduction plan will bring for the public. This knowledge will help government officials decide whether to implement the reduction plan. This article seeks to acquire information about the public willingness to pay (WTP) for the reduction plan, employing the contingent valuation (CV) technique. For this purpose, a total of 1000 households living in South Korea participated in the CV survey in 2017. The data on the WTP were gathered using a dichotomous choice question and analyzed using the spike model. Forty-five percent of the respondents were willing to accept an increase in income taxes to carry out the reduction plan. The mean household WTP estimate was obtained as KRW 3830 (USD 3.41) per annum. The national value expanded from the sample to the population is worth KRW 74.8 billion (USD 66.6 million) per year. This value implies the public value of the reduction plan and can be applied in policy analysis and decision-making concerning the reduction of the incidence of HCS accidents.

Cautionary Sign Analysis of Traffic Sign Data-Set Using Supervised Spiking Neuron Technique

In this paper, 19 cautionary traffic signs were selected as a database and 3 types of conditions have been proposed. The conditions are 5 different time of image taken; hidden region and anticlockwise rotation are all the experiments design that will shows all the errors in producing the it’s mean value and the performance of traffic sign recognition. Initial hypothesis was made as the error will become larger as the interruption getting bigger. Based on the results of the five-different time of image taken, the error gives the best performance; less error when time is between 8am to 12am due to the brightness factors and the sign can be recognize clearly during noon session. The hidden region conditions show good performances of the detection and recognition of the system depend on the lesser coverage of the hidden region introduce on traffic sign because if the hidden region coverage is huge the database will get confuse and take a longer time to do the recognition process. Lastly, in anticlockwise rotation shows that 90o gave large value of error causing the system unable to recognize sign perfectly rather than 135o angle. To sum-up, detection and recognition process are not depending on higher number of angle but the process solely depending on their value of sample for each traffic signs. The error will give the impact towards traffic sign recognition and detection process. In conclusion, SNN can perform the detection and recognition process to all objects as in the future the system will become more stable with the right technique on spiking models and well-developed technology in this field.

Characterizing information-theoretic storage and transfer in continuous time processes.

The characterization of information processing is an important task in complex systems science. Information dynamics is a quantitative methodology for modeling the intrinsic information processing conducted by a process represented as a time series, but to date has only been formulated in discrete time. Building on previous work which demonstrated how to formulate transfer entropy in continuous time, we give a total account of information processing in this setting, incorporating information storage. We find that a convergent rate of predictive capacity, comprising the transfer entropy and active information storage, does not exist, arising through divergent rates of active information storage. We identify that active information storage can be decomposed into two separate quantities that characterize predictive capacity stored in a process: active memory utilization and instantaneous predictive capacity. The latter involves prediction related to path regularity and so solely inherits the divergent properties of the active information storage, while the former permits definitions of pathwise and rate quantities. We formulate measures of memory utilization for jump and neural spiking processes and illustrate measures of information processing in synthetic neural spiking models and coupled Ornstein-Uhlenbeck models. The application to synthetic neural spiking models demonstrates that active memory utilization for point processes consists of discontinuous jump contributions (at spikes) interrupting a continuously varying contribution (relating to waiting times between spikes), complementing the behavior previously demonstrated for transfer entropy in these processes.

Insight into the dynamics of electrons ejected by energetic ions in silicon and its relation to the basics of the inelastic thermal spike model

Abstract A Monte Carlo (MC) event-by-event scheme is used to calculate the temporal and spatial characteristics of electrons in silicon excited by penetrating energetic ions. The ions pass the active region of the device within ∼0.01 fs while interacting with the electrons and leaving behind them a wake of δ-electrons and their cascading secondaries. All electrons with energies Ee > 4 eV slow down to Ee ≤ 4 eV within a time interval of few femtoseconds to hundreds of picoseconds. They are then considered as stopped. Below 4 eV, their interaction with phonons becomes dominant. The results of our simulations help to understand the peculiarities of the processes which take place at these short times. It also becomes clear that one can use the inelastic thermal spike (i-TS) model only several picoseconds after the passing of the ion, and thereby avoid the deeply non-equilibrium stage of ion track evolution which is a serious problem for this model. The calculations, done using our data for the electron-phonon interactions, enable us to find the limits of using the electron-phonon coupling parameter as a constant value (independent of the electronic temperature) in the i-TS model. The latter is a key parameter of the i-TS model. Our analysis also determines the accuracy of other input parameters when the i-TS model is used in combination with molecular dynamics calculations.

Swift heavy ion induced modifications in the structural, optical and methane sensing properties of indium oxide thin films - A comparative study using Ag9+ and O7+ ion irradiation

Thin films of indium oxide grown on quartz substrates were subjected to 100 MeV Ag 9+ and O 7+ ions irradiation. The pristine and swift heavy ions irradiated films were characterized using X-ray Diffraction, Rutherford Backscattering Spectrometry, Scanning Electron Microscopy and UV-Vis Spectroscopy to examine the effect of irradiation with ions having large difference in the values of electronic energy loss (Se) on the structural, microstructural and optical properties of indium oxide thin films. XRD and SEM studies revealed deterioration in crystallinity along with decrease in both crystallite size and grain size upon irradiation with both Ag 9+ and O 7+ ions. However, the decrease in the crystallite size and grain size in comparison to the pristine film was more radical for irradiation with Ag 9+ ions. RBS spectra suggest that the electronic sputtering in the indium oxide films due to SHI irradiation is very less. AFM images illustrate the decrease in surface roughness from 29.8 nm for the pristine film to to 27.4 nm and 26.7 nm on irradiation with 100 MeV O 7+ and Ag 9+ ions at a fluence of 3.3×10 13 ions/cm 2 . Also, UV-Vis study revealed an increment in the value of optical band gap from 3.41 eV for the pristine film to 3.53 and 3.67 eV for indium oxide films irradiated with of 3.3×10 13 ions/cm 2 fluence of O 7+ and Ag 9+ ions respectively. The irradiation induced structural and optical modifications have been explained using the Thermal spike model. Along with the structural and optical properties, sensing properties of the pristine and irradiated films for 100 ppm methane gas at an operating temperature of 300 o C have also been examined and the results have been correlated with the induced structural modifications.

Public preferences for district heating system over individual heating system: a view from national energy efficiency

The price of residential heating from the district heating system is similar to that from the individual heating system in Korea. However, the former is known to be more efficient in terms of national energy consumption than the latter in urban areas with high population density. Because district heating system reduces the total amount of energy consumption by 24% compared to individual heating system. This paper attempts to assess the public preferences for substituting consumption of residential heating produced from individual heating system with that produced from district heating system in terms of national energy efficiency. To apply contingent valuation method, a contingent valuation survey of 1000 households was implemented. Public preferences can be provided price gap, which is willingness to pay (WTP) and the findings can be interpreted as external benefits. For the purpose of mitigating the response effect in eliciting their WTP and increasing statistical efficiency in analyzing the WTP data, we employ a one-and-one-half-bounded dichotomous choice question format. Furthermore, we use the spike model so as to model zero WTP responses. The results show that the mean additional WTP for district heating system over individual heating system is estimated to be KRW 8544 per KRW 100,000 of residential heating. The WTP estimate is statistically significant at the 1% level. Thus, the external benefit of the district heating system over individual heating system in terms of national energy efficiency amounts to about 8.5% of the price for residential heating.

Suppression of underlying neuronal fluctuations mediates EEG slowing during general anaesthesia

The physiological mechanisms by which anaesthetic drugs modulate oscillatory brain activity remain poorly understood. Combining human data, mathematical and computational analysis of both spiking and mean-field models, we investigated the spectral dynamics of encephalographic (EEG) beta-alpha oscillations, observed in human patients undergoing general anaesthesia. The effect of anaesthetics can be modelled as a reduction of neural fluctuation intensity, and/or an increase in inhibitory synaptic gain in the thalamo-cortical circuit. Unlike previous work, which suggested the primary importance of gamma-amino-butryic-acid (GABA) augmentation in causing a shift to low EEG frequencies, our analysis demonstrates that a non-linear transition, triggered by a simple decrease in neural fluctuation intensity, is sufficient to explain the clinically-observed appearance – and subsequent slowing – of the beta-alpha narrowband EEG peak. In our model, increased synaptic inhibition alone, did not correlate with the clinically-observed encephalographic spectral changes, but did cause the anaesthetic-induced decrease in neuronal firing rate. Taken together, our results show that such a non-linear transition results in functional fragmentation of cortical and thalamic populations; highly correlated intra-population dynamics triggered by anaesthesia decouple and isolate neural populations. Our results are able to parsimoniously unify and replicate the observed anaesthetic effects on both the EEG spectra and inter-regional connectivity, and further highlight the importance of neural activity fluctuations in the genesis of altered brain states.

A Digital Hardware Realization for Spiking Model of Cutaneous Mechanoreceptor.

Inspired by the biology of human tactile perception, a hardware neuromorphic approach is proposed for spiking model of mechanoreceptors to encode the input force. In this way, a digital circuit is designed for a slowly adapting type I (SA-I) and fast adapting type I (FA-I) mechanoreceptors to be implemented on a low-cost digital hardware, such as field-programmable gate array (FPGA). This system computationally replicates the neural firing responses of both afferents. Then, comparative simulations are shown. The spiking models of mechanoreceptors are first simulated in MATLAB and next the digital neuromorphic circuits simulated in VIVADO are also compared to show that obtained results are in good agreement both quantitatively and qualitatively. Finally, we test the performance of the proposed digital mechanoreceptors in hardware using a prepared experimental set up. Hardware synthesis and physical realization on FPGA indicate that the digital mechanoreceptors are able to replicate essential characteristics of different firing patterns including bursting and spiking responses of the SA-I and FA-I mechanoreceptors. In addition to parallel computation, a main advantage of this method is that the mechanoreceptor digital circuits can be implemented in real-time through low-power neuromorphic hardware. This novel engineering framework is generally suitable for use in robotic and hand-prosthetic applications, so progressing the state of the art for tactile sensing.

Consumers’ Willingness to Pay for Net-Zero Energy Apartment in South Korea

In South Korea, buildings account for more than 25% of the nation’s total greenhouse gas emissions. Therefore, the government aims to make zero energy buildings mandatory from 2025, onward. For the housing sector, the government has recently built and operated a pilot net-zero energy apartment (NZEA) and plans to expand it to several cities. This article attempts to obtain information about the consumers’ willingness to pay (WTP) for the NZEAs. To this end, households’ additional WTP for the NZEAs over a conventional apartment was investigated, applying the contingent valuation (CV) approach. The data on the WTP were gathered from a CV survey of 1000 interviewees and analyzed, employing a dichotomous choice question and the spike model, respectively. The mean value of the additional WTP is obtained as KRW 0.46 million (USD 424) per m2, which is statistically significant. This value corresponds to 17.0% of the conventional apartment price per m2 (KRW 2.76 million, USD 2436). It can be concluded that the households in South Korea place a significant value on a NZEA over a conventional apartment. In addition, we have investigated the characteristics of consumers which affect the probability that consumers accept additional payment of an amount of money for NZEA over a conventional apartment, finding that higher income earners, higher education, and male consumers have a higher probability.

Temperature dependence of swift heavy ion irradiation induced hillocks in TiO2

Irradiation temperature dependant morphology of near surface latent tracks and surface hillocks in TiO2 was investigated. Irradiation was performed on single crystal [110] oriented rutile using 220 MeV Xe ions to a fluence of 5 × 1010 ions cm−2. Irradiations were performed at 80 K, 300 K, 600 K, 800 K and 1000 K. It was found that average hillock height increased with irradiation temperature although large specimen-to-specimen and hillock-to-hillock size differences were also recorded. Similarly the low density conical zone in the near-surface region of the ion track increased in both length and continuity with increasing temperature. At lower temperatures this zone was found to consist of closely spaced low density pockets that become more densely arranged and almost continuous at 1000 K. Evidence supporting the idea that surface hillocks are due to expelled matter from the track core was found in that larger hillocks are subtended by larger conical zones. These experimental observations were discussed in the framework of a simple model based on the inelastic thermal spike (i-TS) model as well as Bernoulli’s principle which could satisfactorily recreate the observed trends in hillock height and further supports the idea of expelled matter forming hillocks. Strain contrast around latent tracks is mostly absent around the conical zones suggesting some relaxation due to matter expulsion. All hillocks were found to be crystalline and epitaxial with the original crystal surface.

A Multiple-Plasticity Spiking Neural Network Embedded in a Closed-Loop Control System to Model Cerebellar Pathologies.

The cerebellum plays a crucial role in sensorimotor control and cerebellar disorders compromise adaptation and learning of motor responses. However, the link between alterations at network level and cerebellar dysfunction is still unclear. In principle, this understanding would benefit of the development of an artificial system embedding the salient neuronal and plastic properties of the cerebellum and operating in closed-loop. To this aim, we have exploited a realistic spiking computational model of the cerebellum to analyze the network correlates of cerebellar impairment. The model was modified to reproduce three different damages of the cerebellar cortex: (i) a loss of the main output neurons (Purkinje Cells), (ii) a lesion to the main cerebellar afferents (Mossy Fibers), and (iii) a damage to a major mechanism of synaptic plasticity (Long Term Depression). The modified network models were challenged with an Eye-Blink Classical Conditioning test, a standard learning paradigm used to evaluate cerebellar impairment, in which the outcome was compared to reference results obtained in human or animal experiments. In all cases, the model reproduced the partial and delayed conditioning typical of the pathologies, indicating that an intact cerebellar cortex functionality is required to accelerate learning by transferring acquired information to the cerebellar nuclei. Interestingly, depending on the type of lesion, the redistribution of synaptic plasticity and response timing varied greatly generating specific adaptation patterns. Thus, not only the present work extends the generalization capabilities of the cerebellar spiking model to pathological cases, but also predicts how changes at the neuronal level are distributed across the network, making it usable to infer cerebellar circuit alterations occurring in cerebellar pathologies.

The Public Value of Reducing the Incidence of Oil Spill Accidents in Korean Rivers

Oil spill accidents involving cars or boats for transport in rivers can contaminate drinking water sources. During the past ten years, an annual average of forty-six cases of oil spill accidents have occurred in Korean rivers. Because of this, the Korean government is seeking to reduce the incidence of oil spill accidents in rivers by half. This article aims to evaluate the public value of the reduction. Household willingness to pay (WTP) for the reduction was investigated, applying the contingent valuation approach. A survey of 1000 households was carried out in Korea. The data on the WTP were gathered using a dichotomous choice question and analyzed employing the spike model. The mean WTP estimate is obtained as KRW 6188 (USD 5.28) per household per annum, which is statistically meaningful. The total public value expanded to the population amounts to KRW 120.8 billion (USD 103.0 million) per year. The information can be utilized in policy-making and decision-making about the reduction of the incidence of oil spill accidents in rivers by half.

The willingness to pay for removing the microplastics in the ocean – The case of Seoul metropolitan area, South Korea

Microplastics - small plastic particles with less than 5 mm in diameter – in the ocean have become major social concerns among people since it has been found not only harmful to the marine eco-system but also human health. Then, there is an increase in the social demand for appropriate policy by the government. To prepare appropriate countermeasures, it is essential to estimate the environmental damage cost of microplastics in the ocean in advance. Therefore, this study estimates willingness to pay of residents in Seoul metropolitan area in South Korea for removing the microplastics to provide the quantitative information of the environmental damage cost of microplastics in the ocean. This study employed one-and-one-half-bound dichotomous choice with spike model to collect the WTP responses data. To deal with the outliers, we assumed that the distribution of WTP is the contaminated normal distribution, which is heavy-tailed in comparison to normal distribution used in previous studies. In addition, to deal with the numerous zero WTP responses, this study employs the Bayesian censoring regression with data augmentation method. The estimate of the average yearly WTP is KRW 2845.6 (USD 2.59). Additionally, total WTP of households in Seoul metropolitan area was KRW 10.8 billion (USD 9.80 million) annually.

Public Value of Enforcing the PM2.5 Concentration Reduction Policy in South Korean Urban Areas

As the number of cars and the electricity produced from coal-fired generation has been increasing, PM2.5, particles smaller than 2.5 μm in diameter, has become a serious problem in South Korean urban areas. This is especially notable, given that the PM2.5 warning was issued 89 times during 2016. Because of this, the South Korean government is seeking to enforce a policy of reducing the number of PM2.5 warnings by half using various policy instruments from now until 2022. This article tries to obtain information about the public value of the enforcement. For this purpose, household willingness to pay (WTP) for the enforcement is investigated, applying the contingent valuation (CV) approach. A survey of 1000 households was carried out in South Korean urban areas. The data on the WTP were gathered using a dichotomous choice question and analyzed employing the spike model. The mean WTP estimate is obtained as KRW 5591 (USD 4.97) per household per year, which is statistically significant. The total public value expanded to the population amounts to KRW 98.9 billion (USD 87.8 million) per year. The information can be utilized in policy-making and decision-making about the reduction of the PM2.5 concentration.

Pulse-coupled mixed-mode oscillators: Cluster states and extreme noise sensitivity.

Motivated by rhythms in the olfactory system of the brain, we investigate the synchronization of all-to-all pulse-coupled neuronal oscillators exhibiting various types of mixed-mode oscillations (MMOs) composed of sub-threshold oscillations (STOs) and action potentials ("spikes"). We focus particularly on the impact of the delay in the interaction. In the weak-coupling regime, we reduce the system to a Kuramoto-type equation with non-sinusoidal phase coupling and the associated Fokker-Planck equation. Its linear stability analysis identifies the appearance of various cluster states. Their type depends sensitively on the delay and the width of the pulses. Interestingly, long delays do not imply slow population rhythms, and the number of emerging clusters only loosely depends on the number of STOs. Direct simulations of the oscillator equations reveal that for quantitative agreement of the weak-coupling theory the coupling strength and the noise have to be extremely small. Even moderate noise leads to significant skipping of STO cycles, which can enhance the diffusion coefficient in the Fokker-Planck equation by two orders of magnitude. Introducing an effective diffusion coefficient extends the range of agreement significantly. Numerical simulations of the Fokker-Planck equation reveal bistability and solutions with oscillatory order parameters that result from nonlinear mode interactions. These are confirmed in simulations of the full spiking model.

Rate-coded DBN: An online strategy for spike-based deep belief networks

Abstract The memory wall or Von Neumann memory bottleneck decreases the speed of computation in conventional digital platforms. It is due to disharmony of communication speed as well as physical distance between the CPU and memory. In Spiking Neural Network (SNN), both memory and computational elements are integrated into the body of each neuron which provides the possibility of cognitive computing with learning ability in a platform without memory bottleneck. The way of updating the synaptic weights is one of the significant challenges in implementing machine learning methods using spiking model of neurons. Deep Belief learning method recently is used in several state-of-the-art studies due to its potential in robustness computation, pattern recognition, and data classification. In this paper, we use a rate based version of Contrastive Divergence (CD) updating weight rule. Respecting the rate aspect of neural coding, we develop a Spike-Based Deep Belief Network (S-DBN) using Leaky Integrate-and-Fire (LIF) neurons. In experimental evaluations, a two stacked RBMs model is validated using MNIST hand-written digit dataset. The learning accuracy of this architecture is 94.9% yet less than state-of-the-art of Artificial Neural Network (ANN) accuracy, however, quite promising with SNN architecture suitable for hardware implementation. To enhance the accuracy of the network recognition rate, we studied the impacts of notable network parameters for both learning as well as neuron models. Based on the experimental results in this work, choosing optimized parameters for learning rate between 0.008 and 0.01, a frequency of input spikes 18 Hz, the sizes of mini-batches between 25 and 50, and two different membrane voltage thresholds for hidden and visible layers leads to the optimum results in the accuracy rate of the network recognition.

Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network.

Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model).

3 MeV proton irradiation effects on surface, structural, field emission and electrical properties of brass

Abstract Ion-induced modifications of brass in terms of surface morphology, elemental composition, phase changes, field emission properties and electrical conductivity have been investigated. Brass targets were irradiated by proton beam at constant energy of 3 MeV for various doses ranges from 1 × 1012 ions/cm2 to 1.5 × 1014 ions/cm2 using Pelletron Linear Accelerator. Field Emission Scanning Electron Microscope (FESEM) analysis reveals the formation of randomly distributed clusters, particulates, droplets and agglomers for lower ion doses which are explainable on the basis of cascade collisional process and thermal spike model. Whereas, at moderate ion doses, fiber like structures are formed due to incomplete melting. The formation of cellular like structure is observed at the maximum ion dose and is attributed to intense heating, melting and re-solidification. SRIM software analysis reveals that the penetration depth of 3 MeV protons in brass comes out to be 38 µm, whereas electronic and nuclear energy losses come out to be 5 × 10−1 and 3.1 × 10−4 eV/A respectively. The evaluated values of energy deposited per atom vary from 0.01 to 1.5 eV with the variation of ion doses from 1 × 1012 ions/cm2 to 1.5 × 1014 ions/cm2. Both elemental analysis i.e. Energy Dispersive X-ray spectroscopy (EDX) and X-ray Diffraction (XRD) supports each other and no new element or phase is identified. However, slight change in peak intensity and angle shifting is observed. Field emission properties of ion-structured brass are explored by measuring I-V characteristics of targets under UHV condition in diode-configuration using self designed and fabricated setup. Improvement in field enhancement factor (β) is estimated from the slope of Fowler-Nordheim (F-N) plots and it shows significant increase from 5 to 1911, whereas a reduction in turn on field (Eo) from 65 V/µm to 30 V/µm and increment in maximum current density (Jmax) from 12 µA/cm2 to 3821 µA/cm2 is observed. These enhancements in field emission characteristics are correlated with the growth of surface structures, specifically agglomers which are responsible for electric field convergence. Electrical by four probe method has been correlated with maximum current density and decreasing trend is observed with increasing ion doses.

In the Crosshair: Astrometric Exoplanet Detection with WFIRST's Diffraction Spikes

Abstract WFIRST will conduct a coronagraphic program that characterizes the atmospheres of planets around bright nearby stars. When observed with the WFIRST Wide Field Camera, these stars will saturate the detector and produce very strong diffraction spikes. In this paper, we forecast the astrometric precision that WFIRST can achieve by centering on the diffraction spikes of highly saturated stars. This measurement principle is strongly facilitated by the WFIRST H4RG detectors, which confine excess charges within the potential well of saturated pixels. By adopting a simplified analytical model of the diffraction spike caused by a single support strut obscuring the telescope aperture, integrated over the WFIRST pixel size, we predict the performance of this approach with the Fisher-matrix formalism. We discuss the validity of the model and find that astrometric precision is achievable with a single 100 s exposure of an or a star. We discuss observational limitations from the optical distortion correction and pixel-level artifacts, which need to be calibrated at the level of so as to not dominate the error budget. To suppress those systematics, we suggest a series of short exposures, dithered by at least several hundred pixels, to reach an effective per-visit astrometric precision better than . If this can be achieved, a dedicated WFIRST GO program will be able to detect Earth-mass exoplanets with orbital periods of around stars within a few pc as well as Neptune-like planets with shorter periods or around more massive or distant stars. Such a program will also enable mass measurements of many anticipated direct-imaging exoplanet targets of the WFIRST coronagraph and a “starshade” occulter.

Graphitization of amorphous carbon by swift heavy ion impacts: Molecular dynamics simulation

Stable C-C bonds existing in several sp hybridizations place carbon thin films of different structural compositions among the materials most tolerant to radiation damage, for applications in extreme environments. One of such applications, solid state electron stripper foils for heavy-ion accelerators, requires the understanding of the structural changes induced by high-energy ion irradiation. Tolerance of carbon structure to radiation damage, thermal effects and stress waves due to swift heavy ion impacts defines the lifetime and operational efficiency of the foils. In this work, we analyze the consequences of a single swift heavy ion impact on two different amorphous carbon structures by means of molecular dynamic simulations. The structures are constructed by using two different recipes to exclude the correlation of the evolution of sp2-to-sp3 hybridization with the initial condition. Both initial structures contain approximately 60% of sp2-bonded carbon atoms, however, with different degree of clustering of atoms with sp3 hybridization. We simulate the swift heavy ion impact employing an instantaneous inelastic thermal spike model. The analysis of changes in density, bonding content and the number and size of carbon primitive rings reveals graphitization of the material within the ion track, with higher degree of disorder in the core and more order in the outer shell. Simulated track dimensions are comparable to those observed in small angle x-ray scattering measurements of evaporation-deposited amorphous carbon stripper foils irradiated by 1.14 GeV U ions.